Bleg: What are the Predictions of Austrian Cycle Theory?

If you were going to try to adduce evidence with regard to the Mises-Hayek-Garrison “Austrian Business Cycle Theory” what would you expect to see in the expansion, upper turning point and perhaps in the recession itself? Specifically, what would you expect to see in this most recent episode, the so-called Great Recession?

Unfortunately, it would not be helpful to refer to empirical phenomena about which no data is collected. This is a problem with most attempts to measure the elongation of the production structure, for example. But be creative. George Stigler used to say that it is no excuse to say, “The data doesn’t exist.” There may be indirect ways to measure.

Post navigation

23 thoughts on “Bleg: What are the Predictions of Austrian Cycle Theory?”

You would have to scrutinize them closely and standardize or agree on how to code it – but I imagine the BEA’s input-output tables would be very useful for this sort of exercise.

They would also probably help complicate the relatively simply “triangle model” that Garrison presents – because obviously not every final product is going to draw only from the stage of production immediately “before” it in the triangle model.

I’m not too familiar with this literature – I just got Time and Money in the mail yesterday, so I hope to be much more familiar with it soon.

The IO data isn’t perfect, but the triangle model is often framed as a series of different industries (extraction, refining, manufacturing, wholesale, retail, etc.), which makes the use of the IO data natural – so it would at least be a good place to start where there is a data record.

I should say – I flipped through Time and Money last night and one of the things that bugged me was that all of Garrison’s triangles had a constant slope. I know it’s just heuristic, but it’s very unrealistic. In real life, such slopes would not be constant, they’d be steeper or shallower in different place. Monetary changes wouldn’t just rock that single slope back and forth – it would change the shape in different ways at different points, perhaps in extremely unpredictable ways.

Again – it’s a point I’m making with very little understanding of the literature that I’m hoping to remedy – but if my concerns are warranted, it’s something that getting some acutal data from an input-output table might help with, because you could actually see the magnitude of the value added at each stage of produciton.

And if I’m misunderstanding something, I’m sure it will be pointed out to me 🙂

I’m on two minds on the issue because although I recognize that empirical evidence and operational definitions are important, problems in these endeavors are not specific to Austrian economics, as they should be recognized as problems by almost everyone: I know, for instance, of no econometric evidence of monetary non-neutrality (cfr King & Plosser), although I believe that money is always non-neutral.

Anyway, my being on two minds has begotten to contrasting comments.

Comment #1

ABCT has not been proposed as a model so it can’t be directly compared with the data. Only highly aggregate fully specified DSGE models can, and I wouldn’t bet that this comparison with the data is better than playing curve fitting.

However, to look for evidence, I would first look at financial data (there is always plenty of financial data: the credit channel literature is full with econometrics) to check the prociclicality of all financial fragility proxies: financial leverage, maturity mismatch and risk taking. This is the credit creation (and destruction) process at work and it can take millions of different forms (pure bank credit or shadow banking, for instance).

However, credit must be linked to money in order to have ABCT, otherwise it’s Minsky, not Mises. So I would check for the effect of interest rates and monetary aggregates on the financial intermediation proxies. This I think has already been done in the credit channel literature, which I haven’t checked.

Then I would check the structure of production. Unfortunately, I know of only a few papers investigating something similar: Mike Montgomery has shown that capital complementarity explains the lags in the economy’s response to shocks, Mulligan, Wainhouse and Keeler have found something else but I don’t remember the details. It was all about correlations having the expected behavior.

However, it appears that not much evidence is needed to prove that interest-rate sensitive markets are more prone to crises than others, which is all that is required by ABCT: this is a well recognized stylized fact.

Upper and lower turning points cannot be predicted. I would guess that ABCT should predict several years of boom and several months of recessions in standard conditions: that’s what usually happen. There are lots of complicating factors, however: the Japanese ZIRP and Hoover can make things last much longer. I don’t know of anyone capable of predicting turning points, however.

For what concerns the links between monetary, financial and productive data (the third ones are quite scant, because only Austrians are interested in them, while the others are plentiful), data can only show correlations, not causality. So none of these data amounts to corroboration or refutation for any theory.

In few words, Austrians can free ride on the credit channel and look for patterns there. I normally don’t read econometrics papers (it’s deadly boring) and I’ve only seen a few of them, but there are hundreds.

Comment #2

I doubt that the notion of intertemporal disequilibrium can ever be operationalized: it’s not a matter of aggregates but of structures, and structures imply knowledge problems.

Also the notion of monetary non-neutrality has no operational content. All economists can do is to play vector autoregressions and hope noone notices that they prove nothing. The King/Plosser explanation of observed correlations between money and output is as good as any other. There is no empirical evidence that money is non-neutral or neutral, otherwise real business cyclers and new keynesians would have ended their squirmishes decades ago. The problem is empirically undecidable.

While the latter is a problem for all schools of thoughts, the former is a problem only for Austrian economics because others disregard structure. So, let’s disregard money too and all problems are solved. 🙂

Efficiency is another notion I don’t know how to apply to reality: it is a property of fully specified models of artifical economies, not something which can be predicated of reality. When I see something, I can never now whether it could have been better without knowing all the alternatives and all the brute data.

Another example is the natural rate of interest: no one knows it. It’s a theoretical construct with no empirical counterpart. This is a problem both with Austrian and New-Keynesian economics. More than a problem, however, I would say it’s an epistemic property of markets.

Another example is taken from my terrible introductory macro textbook (Blanchard), which wanted me to believe that the 1980-1983 recession falsified the rational expectation theory of stagflations. It falsified nothing, as usual with economic data: newclassicals resorted to the makeshift of distinguishing between credible and non-credible disinflationary attempts and saved their theory. It is a blunder to consider ratex a falsifiable hypothesis.

Before concluding, I would add that new keynesian models have been criticized for excessive plasticity: any contrarian data was rationalized by changing some detail in the model. This is what I call “curve fitting theorizing”, which of course it is an oximoron. David Romer had some issue with this in his textbook, too.

Data collection reveals problems, but offers no solutions. Theories which are so rigid in predictions to yield falsifiable results are usually very poor theories. DSGE models are, on the contrary, very rich theories from this point of view. So rich that they can predict everything, by properly specifying the details.

One problem I’ve had is that the Greenspan era has lasted for so long: ABCT without chinese savers and technological innovation would have predicted a crunch in the ’90s, not 20 years of inflationary booms with some minor slowdowns. This is how data can improve theorizing, by showing expectations requiring second thoughts and additions.

Economic theory is not a theory in the sense of natural sciences, but it is like a language. Languages enable understanding, but are never falsified: they are enriched by interaction with new problems.

The distinction between theory (a mere inquiry into logical structure with limited predicted power) and history (the understanding of complexity) will sooner or later become necessary also among the “mainstream”.

Those who believe that capital heterogeneity has no role in economics are justified to consider Cobb-Douglass production functions only.

Relevance is the only justification for complexity, and the triangle represents the minimum amount of structure that is required to understand ABCT. It doesn’t correspond to anything in the real world, but the same is true for any other model.

Sometimes it is a bad approximation: Garrison’s analysis of overconsumption cannot be understood by using triangles, and submarginal capital goods are excluded from the analysis despite they play a relevant role along the cycle. However, usually it is sufficient(in the statistics meaning: it throws away the irrelevant).

Any economic model with less than billions agents, hundreds of thousands of goods connected by thousands of technological recipes is subject to the “criticism” of not being realistic enough.

PS Sometimes the razor is used in another meaning: “select the simplest theory which explains the stylized facts”. But this would result in selecting putty-like theoretical frameworks with grossly oversimplified conceptual tools which unable the understanding of complex phenomena. This is a criterion for data fitting, not for understanding.

During the boom, I would expect to see an increase in total nominal spending above its prior growth trajectory. That is, if total nominal spending increased about 3% per year prior to the boom, then I would predict a 4-6% rise during the boom. Since this prediction does not fit the facts (so far as I can ascertain), I am inclined to disbelieve that we have witnessed an Austrian business cycle.

I do believe that malinvestment has occurred, but I do not think its primary cause was over-expansionary monetary policy. Perhaps slightly loose monetary policy contributed by creating a more bubbly economy. I agree with Scott Sumner that interest rates are a poor measure of the looseness/tightness of monetary policy.

Austrians, like mainstream economists, seem to be misled by low interest rates. Austrians mistake low interest rates before the recession for loose monetary policy, while mainstream economists mistake low interest rates during the recession for loose monetary policy. Both were wrong if we instead look at total nominal spending.

I’m glad Mario asked the question. I chaired one empirical dissertation on ABCT at NYU. It was ably completed by Charles E. Wainhouse. Using Grainger causality tests, he investigated whether savings “caused” investment. In fact, he found that savings and investment were independent. He inferred that money creation drove investment cycles. (I write this from memory.)

It would be especially interesting if his work were updated. Among other things, it would address the global savings glut hypothesis.

BTW, it is not useful to ascribe beliefs to unnamed Austrians. We get nowhere in such discussions.

To be specific, I have observed no one making the error Lee Kelly ascribes to “Austrians.” During the recent boom, real interest rates were negative. A wide variety of theories — including monetarism and ABCT –predict undesirable consequences from a period of prolonged negative real interest rates.

If one goes back to Prices and Production, Hayek describes a coordination failure produced by credit (money) creation that disturbes plan coordination between savers and investors.

“The interest rate” is a short hand for the entire array of interemporal prices that guide the intertemporal allocation of resources. It is not a question of interest rates being “low” or “high,” but wrong. False price signals generate malinvestment.

ABCT is an extension of Hayek’s work on prices as a communication mechanism. It is at its heart a microeconomic analysis of pricing.

The existence of negative real interest rates does not logically entail discoordination. It could be that negative real interest rates are necessary to equilibrate the supply and demand for loanable funds. Perhaps negative real interests cannot exist indefinitely, but when does “prolonged” become too long? The normal answer would be when real interest rates become positive! But with the assumption that market rates are being artificially suppressed, measuring the innumerable relevent factors seems prohibitively complex.

In any case, I just don’t understand how the Austrian story of the business cycle makes sense unless total nominal spending increases. By artificially expanding the supply of credit, the central bank reduces the market rate of interest. This “stimulates” the demand for capital goods (particularly at earlier stages of production) and the demand for consumer goods at the same time. That is, people do not reduce their spending on consumer goods (or alternative capital goods) to finance the new investment projects, but, in fact, actually increase spending because the benefit of saving has diminished.

If total nominal spending remained stable during the period when this is supposed to have occurred, then any additional spending on capital or consumer goods must have been offset by a reduction in spending elsewhere, i.e. the new investment projects were backed by real savings afterall! That doesn’t mean significant malinvestment did not occur, but there are other causes of malinvestment (see bubbles and government intervention).

“To be specific, I have observed no one making the error Lee Kelly ascribes to “Austrians.” During the recent boom, real interest rates were negative.”

I agree – this is a mistake of lazy people vs. more cognizant people. I don’t think its unheard of for the mistake to be made, but I don’t think it’s especially common in any particular school of thought. Put it this way – nobody’s perspective, properly stated, is contingent on this fallacy. So if anyone does happen to commit it, it doesn’t really tell us about anything more than their care in speaking.

I would question Lee Kelly’s interpretation of what’s being said, potentially. For example, when the Fed drops rates after a bust, someone might say that they are “loosening” policy relative to a counterfactual of them doing nothing (or doing something but less aggressively). That’s not really all that inaccurate if its framed that way – its just important to keep in mind that just because they are “loosening”, it doesn’t mean that policy is “loose”. In other words – Lee Kelly (and Scott Sumner) are using a counterfactual that the monetary authorities both do and don’t have control over when they make their comparison. Other people take what the market is doing as a given, and use the counterfactual of what the monetary authorities would have done if they maintained the status quo. As long as we make sure we keep straight precisely what we’re saying and implying, it doesn’t seem to me to matter all that much. I agree with Jerry – it’s not a hugely pervasive mistake.

I didn’t mean it as anything more than a passing remark. Perhaps I should have been more careful with my word choice, but I plead for leniency given that they are merely part of short comment on a blog.

Jerry,
I think it’d be much easier to update Wainhouse’s now than if someone were doing it twenty years ago. Most of the data is pretty easy to get and its pretty easy to code in stata or some other package.

The ECB and BIS have published some pretty good empirical research on the impact of money and credit growth and their relation to booms and busts.

I think the biggest difficulty with some of the researched mentioned is that its hard to measure what the natural rate of interest should be, so its hard to judge whether monetary policy is too tight or too loose.

Assuming you get an accurate measure how tight/loose monetary policy is, it would be interesting to get the industry portfolios from Ken French’s website and try to determine if industries that have the strongest exposures to long-term interest rates have the strongest returns in the years after monetary policy has been loose/tight.

You are trying to jam ABCT into an alternative framework/model, and then say you “just don’t understand” the story. A loanable funds theory may or may not be a good theory of interest, but it is not the Austrian theory (para 1). The next to last paragraph in my comment was intended to forestall just that move.

In para 2, you tell a story but again it is not Hayek’s (or mine). You are ignoring everything he said in Prices and Production about the the role of of relative prices and the irrelevancy of the price level. Also you ignore the sequencing of changes in demand (which do not occur simultaneously).

It is important to recall that the Austrians (Mises, Hayek, Machlup, at al.) constructed their theories to explain an agreed-upon set of facts. In the History of Economic Analysis, Schumpeter observed that the principal facts of business cycles were known by 1913.

In the 1920s everyone worked feverishly to explain those facts. They weren’t spinning out models in search of facts, but evolving theories to explain the facts. One agreed-upon fact was the sensitivity of long-lived investments, such as construction, to changes in interest rates (as pietro obeserved).

Some version of the turning point or crisis appeared in most theories, because it was how booms turned into busts: suddenly, hence the terminology of boom and bust. Again I agree with Pietro that turning points can’t be predicted.

So good business cycle theories “predicted” the same facts. Now, nearly 100 years later, we have economists who assert we don’t know the facts. And, therefore, the Austrians need to adduce them.

(I was interested to read the FTs interview with Nouriel Roubini in which he expressed an affinity with the Austrian analysis.)

Lee Kelly says the boom was not caused by low interest rates. I disagree. Even before the Fed cut rates to near zero in 2003 and kept them there for over a year, they were too low. During this time there was an excess demand for loanable funds (he seems hung up on equilibrium in that market) thanks to the Fed. This fueled booms in real estate and certain pockets of the stock market (anything having to do with real estate, such as home building stocks), as well as private equity and commodities, to name four markets. (Commodities boomed also because of increasing demand from emerging markets, but that wasn’t the only cause.)
To offer one data point to the question Mario posed, asset groups that boomed experienced prices that rose above their long-term trends. The story of how one investor, John Paulson, intuited that real estate prices were too high and would sooner or later revert to their mean, indeed perhaps fall below it, see the recent book The Greatest Trade Ever.
Jerry O’Driscoll mentions the recent Austrian-oriented FT piece on Roubini; he was also interviewed by Charley Rose and made similar points in the issue before last of Bloomberg Businesssweek. I didn’t see the original interview, but I’m guesssing it might be on Youtube.

I guess for “account falsification” you mean the creation of imaginary profit and loss opportunities due to monetary distortions.

I believe that a historical investigation, however accurate, will not be able to ascertain the relation between a real market price and its ideal distortionless price, because no information is provided as a benchmarket. We only know actual prices: bubbles cannot even be recognized ex post (there is a paper by Eugene White which says that the bull market during the ’20s was not a bubble, for instance, and many are convinced that the e-economy wasn’t a bubble).

All that can be obtained from that kind of data are propositions like “credit easening usually increases capital values” or “credit easening are more effective in increasing the value of durables than of nondurables”, but no information about the correctness of thes prices can be derived from those data.

Mario,
in his paper on the boom-bust of Eastern Europe, Andreas Hoffmann has an interesting graph in which he shows how the production structure was modified in the boom phase: http://mpra.ub.uni-muenchen.de/17797/2/MPRA_paper_17797.pdf (page 41). Is this a proof of the ABCT? I don’t know, but shows more or less the lenghtening of the production structure. Though I don’t know which kind of data are used.

I guess you already know this graph, but it may be a partly answer to your question.

I forgot something more. You might also see, and in this crisis it seems to be clear by some research, that economic agents have massively carried out maturity mismatches, borrowing short and lending long in a massive scale, reaching a globally illiquid position that is unsustainable. This fact has been very well studied by a Spanish economist of the Instituto Juan de Mariana in several comprehensive reports: http://www.juandemariana.org/boletines/99/
The data comes from the FED Flow of Funds and seems to fit very well with his theoretical framework which mainly comes from Austrian ideas.

The surge of total debt and leveraging in the boom, and the deleveraging and reduction of debt in the bust, may also be two more features that can be contrasted with the data.